Monthly Traffic Safety Analysis

68 CRASHES IN
WEYMOUTH, MA
MAY 2025

All metrics benchmarked againstMay 2024

Total crashes in WEYMOUTH decreased by 32% year-over-year, from 100 crashes in May 2024 to 68 crashes in May 2025. This significant reduction in overall crash incidents is the most notable shift. Despite the decrease in total crashes, hit-and-run incidents increased by 75% during the same period.

68

-32.0%was 100

Total Crash Events

0

Persons Killed

34

9.7%was 31

Persons Injured

7

75.0%was 4

Hit-and-Run Crashes

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 2 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the trend for total crashes in WEYMOUTH is downward, with a 32% decrease from 100 crashes in May 2024 to 68 crashes in May 2025. Total injuries, however, saw a slight increase of 9.7%, rising from 31 to 34. Fatalities remained at 0 in both periods, indicating a stable trend for the most severe outcomes.

7

Hit-and-Run Crashes — May 2025

75.0% vs prior (4)

Hit-and-run crashes increased from 4 in May 2024 to 7 in May 2025, representing a 75% increase in count. The hit-and-run rate consequently rose from 4% of total crashes in May 2024 to 10.3% in May 2025. This indicates a notable upward trend in hit-and-run incidents year-over-year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

2

Pedestrians Injured

Prior: 0%

1

Cyclists Injured

Prior: 3-66.7%

31

Motorists Injured

Prior: 2810.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Saturday, with 19 incidents in May 2024, to Thursday, with 15 incidents in May 2025. Similarly, the peak hour for crashes moved from 4p, which had 12 incidents in May 2024, to 3p, which recorded 9 incidents in May 2025. These shifts indicate a change in the temporal distribution of crash occurrences.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at 0 in both May 2024 and May 2025. Serious injury crashes decreased from 2 (2% of total crashes) in the prior period to 1 (1.5% of total crashes) in the current period. Conversely, minor injury crashes increased from 14 (14% of total crashes) to 17 (25% of total crashes), while possible injury crashes decreased from 8 (8% of total crashes) to 5 (7.4% of total crashes).

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes1.5%
-50.0%prior 2
Minor Injury17minor injury crashes25%
21.4%prior 14
Possible Injury5possible injury crashes7.4%
-37.5%prior 8
No Injury43no injury crashes63.2%
-41.9%prior 74

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to 'Failed to yield right of way' increased from 14 in May 2024 to 21 in May 2025, a 50% increase in count. Conversely, 'No improper driving' as a factor decreased significantly from 22 incidents to 10 incidents, a 54.5% reduction. 'Inattention' crashes also saw a substantial decrease, falling from 20 in the prior period to 3 in the current period, an 85% decrease in count.

Officer-Reported Primary Contributing Cause

Failed to yield right of way21 (30.9%)50.0%prior 14
Followed too closely13 (19.1%)-7.1%prior 14
No improper driving10 (14.7%)-54.5%prior 22
Failure to keep in proper lane or running off road7 (10.3%)
Inattention3 (4.4%)-85.0%prior 20
Over-correcting/over-steering3 (4.4%)
Wrong side or wrong way2 (2.9%)
Disregarded traffic signs, signals, road markings1 (1.5%)
Physical impairment1 (1.5%)
Driving too fast for conditions1 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions decreased from 76 in May 2024 to 45 in May 2025. Crashes on dry road surfaces also saw a reduction, from 80 to 57 incidents, while crashes on wet surfaces decreased from 17 to 11. Daylight crashes decreased from 81 to 58, and crashes in dark-lighted roadway conditions decreased from 10 to 8.

Weather

Clear45 (66.2%)
-40.8%prior 76
Cloudy9 (13.2%)
28.6%prior 7
Rain8 (11.8%)
-11.1%prior 9
Clear/Clear3 (4.4%)
Clear/Cloudy1 (1.5%)
Cloudy/Cloudy1 (1.5%)
Cloudy/Rain1 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Weather condition at time of crash

Lighting

Daylight58 (85.3%)
-28.4%prior 81
Dark - lighted roadway8 (11.8%)
-20.0%prior 10
Dark - roadway not lighted1 (1.5%)
Other1 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Lighting condition field

Road Surface

Dry57 (83.8%)
-28.7%prior 80
Wet11 (16.2%)
-35.3%prior 17

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Road surface condition field

Vehicles & Demographics

The total number of persons involved in crashes decreased from 253 in May 2024 to 169 in May 2025, with a corresponding drop in total vehicles from 193 to 128. While most age groups saw a decrease in representation, the 35-44 age group experienced a slight increase from 35 to 36 persons. TOYOTA, the top vehicle make in May 2024 with 36 vehicles, was surpassed by HONDA in May 2025, which had 19 vehicles involved compared to TOYOTA's 17.

Top Vehicle Makes (128 vehicles)

1
HONDA19 (14.8%)
-20.8%prior 24
2
TOYOTA17 (13.3%)
-52.8%prior 36
3
JEEP11 (8.6%)
-8.3%prior 12
4
FORD10 (7.8%)
-61.5%prior 26
5
CHEVROLET10 (7.8%)
-41.2%prior 17
6
SUBARU8 (6.3%)
60.0%prior 5
7
NISSAN7 (5.5%)
-53.3%prior 15
8
GMC5 (3.9%)
0.0%prior 5
9
HYUNDAI4 (3.1%)
-42.9%prior 7
10
LEXUS4 (3.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Vehicle unit records

5 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (163 persons with recorded sex)

Male94 (57.7%)
-13.0%prior 108
Female69 (42.3%)
-42.0%prior 119

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph speed zones decreased from 43 in May 2024 to 30 in May 2025. Similarly, incidents in 35 mph zones decreased from 19 to 15, and crashes in 60 mph zones decreased from 9 to 6. No fatal crashes were recorded in any speed zone during either period, maintaining a consistent fatal rate of 0.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Posted speed limit at crash location

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Massachusetts Crash Data (MassDOT CDV), accessed programmatically via the Arcgis_yearly Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.

Data Retrieval

  • Access method: Arcgis_yearly Open Data API (SoQL queries)
  • Data format: Structured JSON via REST API
  • Record types queried: Crash events, person records, and vehicle unit records
  • Date filter applied: 2025-05-01 through 2025-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-05-01 through 2025-05-31 (31 days)
  • Geographic scope: WEYMOUTH, MA
  • Total crash records analyzed: 68
  • Total persons involved: 169
  • Total vehicles involved: 128

Analytical Methodology

  • Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
  • Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
  • Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
  • Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
  • Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
  • Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
  • AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.

Limitations & Disclaimers

  • Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
  • Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
  • Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
  • AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
  • Percentages are calculated from reported data and are subject to rounding.

Non-Affiliation Disclosure

This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.

Data License

The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.

Corrections & Feedback

If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.

Suggested Citation

ThatCarHitMe.com (Injuria.ai). "WEYMOUTH, MA Crash Intelligence Report: May 2025." Published June 21, 2026. Reporting period: 2025-05-01 to 2025-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/weymouth/may-2025-report

About the Publisher

ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.

Questions about this report's data or methodology: data@injuria.ai

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Weymouth, MA Crash Report — May 2025 | ThatCarHitMe.com